Machine learning and deep learning predictive models for the stock market

Accurately predicting the movement of stock prices can help people make more informed investment decisions and thus obtain higher returns. They can also assess market trends, develop investment strategies and provide investment advice. In this paper, we used 5 models including Random Forest, XGBoost, ANN, RNN, LSTM to predict and verify the fit of 3 companies (AMZN, BABA and MSFT). It is found that LSTM and random forest model can predict well in most cases. The development of the financial industry does have some shortcomings, and the future financial field will be a field full of challenges and opportunities, so some machine learning and deep learning methods can be used to solve the prediction and modeling problems of financial aspects such as the stock market.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-09-02
DOI
https://doi.org/10.1051/shsconf/202419602007/pdf
Primary Topic
Stock Market Forecasting Methods
Type
article
Field-Weighted Citation Impact
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article

Machine learning and deep learning predictive models for the stock market

Springer Link (Chiba Institute of Technology)
Stock Market Forecasting Methods
article

Machine learning and deep learning predictive models for the stock market

article en

Abstract

Accurately predicting the movement of stock prices can help people make more informed investment decisions and thus obtain higher returns. They can also assess market trends, develop investment strategies and provide investment advice. In this paper, we used 5 models including Random Forest, XGBoost, ANN, RNN, LSTM to predict and verify the fit of 3 companies (AMZN, BABA and MSFT). It is found that LSTM and random forest model can predict well in most cases. The development of the financial industry does have some shortcomings, and the future financial field will be a field full of challenges and opportunities, so some machine learning and deep learning methods can be used to solve the prediction and modeling problems of financial aspects such as the stock market.

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 58%
Stock Market Forecasting Methods
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